The average wait time to get seated at a popular restaurant in the city on a Friday night is 15 minutes. Is the mean wait time greater for men who wear a tie? Wait times for 13 randomly selected men who were wearing a tie are shown below. Assume that the distribution of the population is normal. 16, 17, 16, 13, 17, 16, 13, 13, 14, 17, 16, 15, 16 What can be concluded at the the a = 0.01 level of significance level of significance? a. For this study, we should use test for a population mean b. The null and alternative hypotheses would be: Hạ: Select an ansver Seiect an ansver c. The test statistic| (please show your answer to 3 decimal places.) (Please show your answer to 4 decimal places.) d. The p-value- e. The p-value is > f. Based on this, we should ta to reect s. Thus, the final conclusion is that.. v the null hypothesis. O The data suggest the populaton mean is significantly more than 15 at a = 0.01, so there is statistically significant evidence to conclude that the population mean wait time for men who wear a tie is more than 15. The data suggest that the population mean wait time for men who wear a tie is not significantly more than 15 at a - 0.01, so there is statistically insignificant evidence to conclude that the population mean wait time for men who wear a tie is more than 15. O The data suggest the population mean is not significantly more than 15 at a ▪ 0.01, so there is statistically insignificant evidence to conclude that the population mean wait time for men ual to 1K

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Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.